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Usher: Enabling Quality Data Collection on Mobile Phones
Kuang Chen, Ph.D Student, EECS, UC Berkeley
Abstract: Recently, the Director General of the...
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Usher: Enabling Quality Data Collection on Mobile Phones
Kuang Chen, Ph.D Student, EECS, UC Berkeley
Abstract: Recently, the Director General of the World Health Organization likened the lack of quality health information in low income countries to a "gathering storm", saying, "to make people count, we first need to be able to count." All over the world, the pervasiveness of cellular networks is enabling mobile-based data collection. Community health workers armed with commodity phones are starting to visit the most rural and isolated places to promote health and gather data in mobile forms. Among their challenges, data quality ranks high: a recent study found that mobile-based data quality was ten-times worse than dictation to a human operator. In this talk, we will present an overview of Usher, a system to address this challenge.
Usher automates form design, filling, and data quality assurance for mobile phones and other non-traditional data entry settings. Rather than relying on domain experts, Usher learns a probabilistic model over form questions using existing form data. Usher then applies this model at every step of the data entry process to ensure high quality. Before entry, it induces a form layout that captures the most important data values of a form instance as quickly as possible. During entry, it dynamically adapts the form to the values being entered, and provides real-time feedback to guide the data enterer toward more likely values, and to avoid errors. After entry, it re-asks questions that it deems likely to have been entered incorrectly. We evaluated Usher using two real-world data sets. Results demonstrate that each component has the potential to improve data quality considerably, and at a reduced cost when compared to current practice.
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Beyond Market Prices: Improving the Productivity and Profitability of Small Farmers
Tapan Parikh, Asst Professor, School of Information, UC Berkeley
Abstract: Improving the productivity and profitability of smallholders farmers is the main pathway for economic development of many of the world's poorer countries. It has been noted that improved access to timely and relevant knowledge and information could significantly improve the economic opportunities available to such farmers. However, most research to date has focused on providing and studying the impact of only one kind of information - market prices. While clearly important, this ignores many other kinds of information relevant to small farmers, especially when institutional, infrastructural and knowledge limitations reduce small farmers' capacity to capitalize market information. In this talk, I describe two systems that address other information limitations faced by small farmers, and the institutions that serve them. The first system, Avaaj Otalo, allows small farmers in Gujarat, India to access timely and relevant agricultural advice via a voice-based service accessed via a conventional phone line. In the first three months of a pilot evaluation, with access provided to fifty incoming phone numbers, the system has received an average of 3500 calls per month. The second system, Digital ICS, allows an organic, fair trade coffee cooperative in Oaxaca, Mexico to monitor quality and certification requirements for each of its members, and to be more responsive to the issues they face. Field inspectors document growing condictions, and capture the questions and comments of farmers using a mobile phone-based data collection application. In a six-month trial deployment, the system has significantly reduced data collection and processing time, demonstrating the potential to save the cooperative approximately $10,000 a year in labor costs, while providing the cooperative with richer data about its members as an added benefit.
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